COVID-19 Interactive Analysis Dashboard¶

# importing libraries

from __future__ import print_function
from ipywidgets import interact, interactive, fixed, interact_manual
from IPython.core.display import display, HTML

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import plotly.express as px
import folium
import plotly.graph_objects as go
import seaborn as sns
import ipywidgets as widgets

sorted_country_df = country_df.sort_values('confirmed', ascending= False)

Slide to check for the worst hit countries¶

# # plotting the 20 worst hit countries

def bubble_chart(n):
    fig = px.scatter(sorted_country_df.head(n), x="country", y="confirmed", size="confirmed", color="country",
               hover_name="country", size_max=60)
    fig.update_layout(
    title=str(n) +" Worst hit countries",
    xaxis_title="Countries",
    yaxis_title="Confirmed Cases",
    width = 700
    )
    fig.show();

interact(bubble_chart, n=10)

ipywLayout = widgets.Layout(border='solid 2px green')
ipywLayout.display='none'
widgets.VBox([fig], layout=ipywLayout)

def plot_cases_of_a_country(country):
    labels = ['confirmed', 'deaths']
    colors = ['blue', 'red']
    mode_size = [6, 8]
    line_size = [4, 5]
    
    df_list = [confirmed_df, death_df]
    
    fig = go.Figure();
    
    for i, df in enumerate(df_list):
        if country == 'World' or country == 'world':
            x_data = np.array(list(df.iloc[:, 20:].columns))
            y_data = np.sum(np.asarray(df.iloc[:,4:]),axis = 0)
            
        else:    
            x_data = np.array(list(df.iloc[:, 20:].columns))
            y_data = np.sum(np.asarray(df[df['country'] == country].iloc[:,20:]),axis = 0)
            
        fig.add_trace(go.Scatter(x=x_data, y=y_data, mode='lines+markers',
        name=labels[i],
        line=dict(color=colors[i], width=line_size[i]),
        connectgaps=True,
        text = "Total " + str(labels[i]) +": "+ str(y_data[-1])
        ));
    
    fig.update_layout(
        title="COVID 19 cases of " + country,
        xaxis_title='Date',
        yaxis_title='No. of Confirmed Cases',
        margin=dict(l=20, r=20, t=40, b=20),
        paper_bgcolor="lightgrey",
        width = 800,
        
    );
    
    fig.update_yaxes(type="linear")
    fig.show();

Check the details of your country or the World¶

Enter the name of your country(in capitalized format(e.g. Italy)) and world for total cases

interact(plot_cases_of_a_country, country='World')

ipywLayout = widgets.Layout(border='solid 2px green')
ipywLayout.display='none' # uncomment this, run cell again - then the graph/figure disappears
widgets.VBox([fig], layout=ipywLayout)

10 worst hit countries - Confirmed cases¶

px.bar(
    sorted_country_df.head(10),
    x = "country",
    y = "confirmed",
    title= "Top 10 worst affected countries", # the axis names
    color_discrete_sequence=["pink"], 
    height=500,
    width=800
)

10 worst hit countries - Death cases¶

px.bar(
    sorted_country_df.head(10),
    x = "country",
    y = "deaths",
    title= "Top 10 worst affected countries", # the axis names
    color_discrete_sequence=["pink"], 
    height=500,
    width=800
)

10 Worst hit countries - Recovering cases¶

px.bar(
    sorted_country_df.head(10),
    x = "country",
    y = "recovered",
    title= "Top 10 worst affected countries", # the axis names
    color_discrete_sequence=["pink"], 
    height=500,
    width=800
)

Global spread of COVID-19¶

import math
world_map = folium.Map(location=[11,0], tiles="cartodbpositron", zoom_start=2, max_zoom = 6, min_zoom = 2)


for i in range(0,len(confirmed_df)):
    if (-360<confirmed_df.iloc[i]['lat']<360 and -360<confirmed_df.iloc[i]['long']<360 ):
      folium.Circle(
        location=[confirmed_df.iloc[i]['lat'], confirmed_df.iloc[i]['long']],
        fill=True,
        radius=(int((np.log(confirmed_df.iloc[i,-1]+1.00001)))+0.2)*50000,
        color='red',
        fill_color='indigo',
        tooltip = "<div style='margin: 0; background-color: black; color: white;'>"+
                    "<h4 style='text-align:center;font-weight: bold'>"+confirmed_df.iloc[i]['country'] + "</h4>"
                    "<hr style='margin:10px;color: white;'>"+
                    "<ul style='color: white;;list-style-type:circle;align-item:left;padding-left:20px;padding-right:20px'>"+
                        "<li>Confirmed: "+str(confirmed_df.iloc[i,-1])+"</li>"+
                        "<li>Deaths:   "+str(death_df.iloc[i,-1])+"</li>"+
                        "<li>Death Rate: "+ str(np.round(death_df.iloc[i,-1]/(confirmed_df.iloc[i,-1]+1.00001)*100,2))+ "</li>"+
                    "</ul></div>",
        ).add_to(world_map)

world_map